AI Engineer
Role details
Job location
Tech stack
Job description
Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuses on implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions., AI Agent Engineering
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Design and implement AI agents, including:
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Retrieval (RAG)
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Orchestration workflows
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Tool/function invocation
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Policy-based routing
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Build evaluation frameworks for accuracy, latency, and reliability
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Implement observability and monitoring for agent lifecycle AI Platform Integration
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Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)
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Build abstraction layers to support multi-model and multi-provider architectures
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Optimize model usage for performance, cost, and latency Cloud-Native Development
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Develop scalable services using:
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Microservices architecture
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Containers (Docker, Kubernetes)
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Serverless and event-driven patterns
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Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)
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Ensure production readiness, logging, monitoring, and fault tolerance Application Development
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Build and deploy AI-powered applications aligned to business workflows
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Integrate AI systems into existing enterprise platforms and APIs
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Develop backend services and APIs supporting agent workflows Testing & Performance
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Define and execute test strategies for AI systems
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Measure system performance (latency, throughput, accuracy, cost)
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Debug and optimize production systems
Requirements
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10+ years of software engineering experience
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Strong experience with cloud-native systems (APIs, microservices, containers, serverless)
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Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)
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Proficiency in Python, Java, or similar backend languages Experience with:
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CI/CD pipelines
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Infrastructure as code
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Monitoring and observability tools
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Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar) Preferred Experience
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Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)
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Experience designing multi-agent or distributed AI systems
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Familiarity with enterprise-scale system integration
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Experience optimizing AI workloads for cost and performance Scope & Expectations
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100% hands-on engineering role (no people management)
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Deliver production-quality code and deployments
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Work within existing architecture and engineering standards
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Collaborate with client and internal engineering teams as needed
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Participate in technical design discussions (implementation-focused)